ARTIFICIAL INTELLIGENCE AND AUTOMATION IN ACCOUNTING: A BIBLIOMETRIC ANALYSIS

Yıl 2026, Cilt: 25 Sayı: 77, 107 - 128, 19.01.2026

Tuğçe Karayiğit Kiriktir

https://doi.org/10.55322/mdbakis.1695727

Öz

The rapid advancement of automation and artificial intelligence–based technologies has significantly contributed to a profound transformation and development process in the field of accounting, as in many other sectors. The increasing influence of these technologies in accounting enables financial transactions to be carried out in a more efficient and effective way. However, despite the remarkable growth in their use within accounting practices in recent years, the limited number of academic studies on this subject constitutes the main motivation for this research.
In this context, the primary aim of the study is to systematically examine the scientific publications in the literature related to the concepts of automation and artificial intelligence in the field of accounting through bibliometric analysis. Within the scope of the research, a total of 372 scientific studies published between 1986 and 2025 were analyzed bibliometrically using the “biblioshiny” interface of the “bibliometrix” package in the R program, based on data obtained from the Web of Science database.
The findings derived from the bibliometric analysis reveal annual publication trends, influential authors, journals, countries, keywords, trending articles, citation patterns, and major collaboration networks. Moreover, it was observed that in recent years, the growing interest of researchers in this topic has been accompanied by a steady increase in the number of related studies.

Anahtar Kelimeler

Accounting , Automation , Artificial Intelligence , Bibliometric Analysis.

MUHASEBE ALANINDA YAPAY ZEKA VE OTOMASYON: BİBLİYOMETRİK BİR ANALİZ

Öz

Otomasyon ve yapay zeka temelli teknolojilerin hızla ilerlemesi, birçok sektörde olduğu gibi muhasebe alanında da köklü bir dönüşümün ve gelişim sürecinin ortaya çıkmasına önemli ölçüde katkı sağlamıştır. Otomasyon ve yapay zeka teknolojilerinin muhasebe alanındaki etkisinin giderek artması, finansal işlemlerin daha verimli, işlevsel ve etkin bir biçimde yürütülmesini mümkün kılmaktadır. Bununla birlikte, bu teknolojilerin muhasebe uygulamalarında kullanımının son yıllarda belirgin biçimde artmasına rağmen, konuya ilişkin akademik araştırmaların halen sınırlı olması, bu çalışmanın temel motivasyonunu oluşturmaktadır. Bu bağlamda çalışmanın temel amacı, muhasebe alanında otomasyon ve yapay zeka kavramlarına yönelik literatürde yer alan bilimsel yayınların bibliyometrik analiz yöntemiyle sistematik olarak incelenmesidir. Araştırma kapsamında, 1986-2025 yılları arasında yayınlanmış olan 372 adet bilimsel çalışma, Web of Science veri tabanında R programında “bibliometrix” paketindeki “biblioshiny” arayüzü kullanılarak bibliyometrik analiz yapılmıştır. Çalışma sonucunda bibliyometrik analiz yoluyla elde edilen bulgulara göre yıllık yayın sıklığı, etkili yazarlar, dergiler, ülkeler, anahtar kelimeler, trend olan makaleler, atıf analizi ve önemli ağ iş birlikleri belirlenmiştir. Ayrıca son yıllarda araştırmacıların konuya olan ilgisinin artması ile birlikte yapılan çalışmaların arttığı gözlemlenmiştir.

Anahtar Kelimeler

Muhasebe , Otomasyon , Yapay Zeka , Bibliyometrik Analiz

Kaynakça

• Ajayi-Nifise, A., Odeyemi, O., Mhlongo, N., Victoria, C., Elufioye, O., & Awonuga, K. (2024). The future of accounting: Predictions on automation and AI integration. World Journal of Advanced Research and Reviews, 11(01), 399-407.
• Ali, Z., & Mustafa, G. (2023). On Accounting Firms Serving Small and Medium-Sized Enterprises: A Review, Synthesis and Research Agend. Australian Accounting Review,106(33), 313–332.
• AlKoheji, A., & Al-Sartawi, A. (2023). Artificial Intelligence and Its Impact on Accounting Systems.
• Andiola, L., Masters, E., & Norman, C. (2020). Integrating technology and data analytic skills into the accounting curriculum: Accounting department leaders. Journal of Accounting Education, (50), 1-20.
• Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.
• Carnegie, G., Parker, L., & Tsahuridu, E. (2021). It's 2020: What is accounting today? Australian Accounting Review, 96(31), 65–73.
• Chukwuani, V., & Egiyi, M. (2020). Automation of accounting processes: Impact of artificial intelligence. International Journal of Research and Innovation in Social Science, 5(8), 444-449.
• Damerci, H., & Salimi, A. (2021). Mediating effect of use perceptions on technology readinessand adoption of artificial intelligence in accounting. Accountıng Educatıon, 30(2), 107–130.
• Elnakeeb, S., & Elawadly, H. (2024). Automation and artificial intelligence in accounting: a comprehensive bibliometric analysis and future trends. Journal of Financial Reporting and Accounting, 1-36.
• Harrast, S. A. (2020). Robotic process automation in accounting systems. Journal of Corporate Accounting & Finance, 31(4), 209-213.
• Hu, B., & Wu, Y. (2023). AI-based compliance automation in commercial bank: how the silicon valley bank provided a cautionary tale for future ıntegration. International Research in Economics and Finance. 7(1), 13-20.
• Jiang, Y., Li, X., Luo, H., & Yin, S. (2022). Quo vadis artifcial intelligence? Discover Artifcial Intelligence, 2(4), 1-19.
• Khan, D. Pattnaik, R. Ashraf, I. Ali, Kumar, S. & Donthu N. (2021). Value of special issues in the journal of business research: A bibliometric analysis Journal of Business Research, (12)5, 295-313.
• LeCun, Y., Bengio, Y., & Hinton , G. (2015). Deep learning. Nature 521, 436–444.
• Li, B., Yu, J., Zhang, J., & Ke, B. (2015). Detecting Accounting Frauds in Publicly Traded U.S. Firms. A Machine Learning Approach., 173–188.
• Donthu, N., Kumar, S., Pattnaik, D., & Lim, W. M. (2021). A bibliometric retrospection of marketing from the lens of psychology. Insights from Psychology & Marketing. Psychology & Marketing, 38(5), 834–865.
• Nikitas, A., Michalakopoulou, K., Njoya, E., & Karampatzakis, D. (2020). artificial ıntelligence, transport and the smart city: definitions and dimensions of a new mobility era. Sustainability, 2-19.
• De Melo, S. Amajunepa, E. Santos, E. De Melo, André X. & Aragão; D., (2024). Artıfıcıal ıntellıgence in accounting: a bibliometrıc analysis. Aracê, 6(1), 388-408.
• Oyewo, B. (2022). Contextual factors moderating the impact of strategic management accounting on competitive advantage. Journal of Applied Accounting Research,23(5), 921-949.
• Passas, I. (2024). Bibliometric analysis: the main steps. Encyclopedia, 4(2), 1014–1025.
• Peng, Y., Ahmad, S., Al Shaikh, M., Daoud, M., & Alhamdi, F. (2023). Riding the waves of artificial ıntelligence in advancing accounting and ıts ımplications for sustainable development goals. Sustainability, 15(19), 1-12.
• R Core Team (2024). R: A language and environment for statistical computing r foundation for statistical computing, Vienna, Austria.
• Rahman, M., & Zhu, H. (2023). Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China. Accounting & Finance, 63(3), 3455–3486.
• Ribeiro, J., Lima, R., Eckhardt, T., & Paiva, S. (2021). robotic process automation and artificial ıntelligence in ındustry 4.0 – a literature review. Procedia Computer Science, 181(1), 51–58.
• Russell, S., & Norvig, P. (2020). Artificial Intelligence A modernapproach. 1-119: Pearson Education.
• Saliy, V., Ishchenko,, O., Bush, V., Gladysheva , E., & Abyzova , E. (2020). Accounting and analytical systems as an ıntegral element of contemporary accounting. Frontier Information Technology and Systems Research in Cooperative Economics, 316, 739–746.
• Schweitzer, B. (2024). Artificial ıntelligence (aı) ethics in accounting. Journal of Accounting, Ethics & Public Policy, 25(1), 67-102.
• Tavares, M., Azevedo, G., Marques, R., & Bastos, M. (2023). Challenges of education in the accountingprofession in the Era 5.0: A systematic review. Cogent Business & Management, 10(2), 1-30.
• Varma, A., Piedepalumbo, P., & Mancini, D. (2021). Big data and accounting: A bibliometric study. International Journal of Digital Accounting Research, 21, 203–238.